Guest Post by Willis Eschenbach
The discussion of the 1998 Mann “Hockeystick” seems like it will never die. (The “Hockeystick” was Dr. Michael Mann’s famous graph showing flatline historical temperatures followed by a huge modern rise.) Claims of the Hockeystick’s veracity continue apace, with people doggedly wanting to believe that the results are “robust”. I thought I’d revisit something I first posted and then expanded on at ClimateAudit a few years ago, which are the proxies in Michael Mann et al.’s 2008 paper, “Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia” (M2008). This was another salvo in Mann’s unending attempt to revive his fatally flawed 1998 “Hockeystick” paper. I used what is called “Cluster Analysis” to look at the proxies. Cluster analysis creates a tree-shaped structure called a “dendrogram” that shows the similarity between the individual datasets involved. Figure 1 shows the dendrogram of the 95 full-length proxies used in the M2008 study:
Figure 1. Cluster Dendrogram of the 95 proxies in the Mann 2008 dataset which extend from the year 1001 to 1980. The closer together two proxies are in the dendrogram, the more similar they are. Absolute similarity is indicated by the left-right position of the fork connecting two datasets. The names give the dataset abbreviation as used by Mann2008, the type (e.g. tree ring, ice core) the location as lat/long, the name of the princiipal investigator, and if tree rings the species abbreviation (e.g. PIBA, PILO).
What can we learn from this dendrogram showing the results of the cluster analysis of the Mann 2008 proxies?
First let me start by describing how the dendrogram is made. The program compares all possible pairs of proxies, and measures their similarity. It selects the most similar pair, and draws a “fork” that connects the two.
Take a look at the “forks” in the dendrogram. The further to the left the fork occurs, the more similar are the pairs. The two most similar proxy datasets in the whole bunch are ones that are furthest to the left. They turn out to be the Tiljander “lightsum” and “thicknessmm” datasets.
Once these two are identified, they are then averaged. The individual proxy datasets are replaced by the average of the two. Then the procedure is repeated. This time it compares all possible remaining pairs, including the average of the first two as a single dataset. Again the most similar pair is selected, marked with a “fork” (slightly to the right of the first fork), and averaged. In the dataset above, the most similar pair is again among the Tiljander proxies. In this case, the pair consists of the “darksum” proxy on the one hand, and the average of the two Tiljander proxies from the first step on the other hand. These two are then removed and replaced with their average.
This procedure is repeated over and over again, until all of the available proxies have been averaged together and added to the dendrogram and it is complete.
In this case, the clustering is clearly not random. In general a cluster is composed of measurements of similar things in a single geographical area (e.g. Argentinian Cypress tree rings). In addition, the proxies tend to cluster by proxy type (e.g. speleothems and sediments vs. tree rings).
Next, the dendrogram can be read from the bottom up to show which groups of proxies are most dissimilar to the others. The more outlying and more unusual group a group is, the nearer it is to the top of the dendrogram.
Next, note that many of the groups of proxies are much more similar to each other than they are to any of the other proxies. In particular the bristlecone “stripbark pines” end up right at the top of the dendrogram, because they are the most atypical group of the lot. Only when there is absolutely no other choice are the bristlecones at the top of the dendrogram added to the dendrogram.
So how does this type of analysis clarify whether the “Hockeystick” is real? The question at issue all along has been, is the “hockeystick” shape something that can be seen in a majority of the proxies, or is it limited to a few proxies? This is usually phrased as whether the results are “robust” to the removal of subsets of the proxies. And as usual in climate science, there are several backstories to this question of “robustness”.
The first backstory on this question is that well prior to this study, the National Research Council (2006) “Surface Temperature Reconstructions for the Last 2,000 Years” recommended that the bristlecone and related “stripbark” pines not be used in paleotemperature reconstructions. This recommendation had also been made previously by other experts in the field. The problem for Mann, of course, is that the hockeystick signal doesn’t show up much when one leaves out the bristlecones. So like a junkie unable to resist going back for one last fix, Dr. Mann and his adherents have found it almost impossible to give up the bristlecones.
The next backstory is that a number of the bristlecone proxy records collected by Graybill have failed replication, as shown by the Ababneh Thesis. Not only that, but one of the authors of M2008 (Malcolm Hughes) had to have known that, because he was on her PhD committee … so the M2008 study used proxies that were not only not recommended for use, but proxies not recommended for use that they knew had failed replication. Bad scientists, no cookies.
The final backstory is that the Tiljander proxies a) were said by the original authors to be hopelessly compromised in recent times and who advised against their use as temperature proxies, and b) were used upside-down by Mann (what he called warming the proxies actually showed as cooling).
With all of that as prologue, Figure 2 shows the average signals of the clusters of normalized proxies (averaged after each proxy is normalized to an average of zero and a standard deviation of one). See if you can tell where the Hockeystick shaped signal is located …
Figure 2. Left column shows average signals of the clusters of proxies shown in Figure 1, from the year 1001 to 1980. Averages are of the cluster to which each is connected by a short black line.
You can see the problems with the various Tiljander series, which are obviously contaminated … they go off the charts in the latter part of the record. In addition, if the Tiljander data were real it would be saying record cold, not record hot, but the computational method of Mann et al. flipped it over.
The reason for the unending addiction of Mann and his adherents to certain groups of proxies becomes obvious in this analysis. The hockeystick shape is entirely contained in a few clusters—the Greybill bristlecones and related stripbark species, the upside-down Tiljander proxies, and a few Asian tree ring records. The speleothems and lake sediments tell a very different story, one of falling temperatures … and in most of the clusters, there’s not much of a common signal at all. Which is why the attempts to rescue the original 1998 “hockeystick” have re-used and refuse to stop re-using those few proxies, proxies which are known to be unsuitable for use in paleotemperature reconstructions. They refuse to stop recycling them for a simple reason … you can’t make hockeysticks without those few proxies.
To sum up. Is the mining of “hockeystick” shaped climate reconstructions from this dataset a “robust” finding?
Not for me, not one bit. While you can get a hockeystick if you waterboard this data long enough, the result is a chimera, a false result of improper analysis. The hockeystick shaped signal is far too localized, and occurs in far too few of the clusters, to call it “robust” in any sense of the word.
w.
PS – The entire saga of the Ababneh Thesis, along with lots and lots of other interesting information, is available over at ClimateAudit. People who want to improve their knowledge about things like the proxy records and the Climategate FOI requests and the whole climate saga should certainly do their homework at ClimateAudit first … because in the marvelous world of Climate Science, things are rarely what they seem.
[UPDATE] Some commenters asked for the data, my apologies for not providing it. It is located at the NOAA Paleoclimate repository here.
Nice review – I hadn’t seen this analysis of the hockey stick data sets laid out this neatly before. Too bad material like this never makes the news – it might help reduce the nonsense.
Nice. Very clear. Thanks Willis!
This is a very useful breakdown of the work (cough) that Mann does. Mann is exactly like a kid who just can’t stop taking cookies from the cookie jar. It doesn’t matter what happens, he just keeps going back for more.
I have never found a reconstruction that was independent of Mann that has EVER shown a hockey stick. That is everything that needs to be known about the *robust* method of Mann.
Great explanation for people like me who have no technical background. It never ceases to amaze me how the team continue to cling to their precious icon, even as it melts slowly into the category of science fiction.
Another interesting and very informative piece, keep em coming Willis
I take it that Mann ignored the data from “Speleotherms and Lake Sediments” which shows an upside down hockey stick and the data from everything else which shows precisely nothing. This is the “science” of Man Made Global Warming.
Excellent analysis – very well presented. Kill it with fire indeed.
Nice work Willis. Climategate got me interested in this stuff, but it has been a long-haul since then getting up to speed. Things like how Mann et al have treated Tiljander alone are mind-boggling – if it weren’t for the apparently blatant incompetence of applying the data upside-down, one would be tempted to infer outright fraud.
I remember a heated thread over at CA where the Tiljander defenders came out on one side, amac and others on the other side and I just could not believe seemingly intelligent people (gosh they may very well have been University academics) arguing for the Teljander proxies. I believe later S. Mosher did a very funny parody of that post here at WUWT based on Abbot and Costello’s “Who’s on First”.
That was another turning point in my understanding – (apparently) well educated, well spoken individuals are entirely willing to vigorously defend an obvious error…something weird is going on in Climate Science.
This is high-level tree geek stuff. Thanks for the analysis.
Nice Willis. Thanks.
The dendrogram is an interesting concept that seems able to group foibles together. I see the big spike at the end of the Tiljander-derived chart that seems even more hockeystick-ish than the Greybill bristlecone chart above it. Interesting comment that the Tiljander data was “haplessly compromised in recent times” according to the original authors, but that Mann used them anyhow in a sort of inverse manner. It would be interesting to learn why, if properly used, the Tiljander proxies would have indicated cooling instead of warming.
But maybe tide is turning — our Governor Christie has just pulled NJ out of the “Cap And Trade” agreement that has been in effect for several northeastern States (excluding PA) that Christie said was costing the average NJ utility user (like me) an EXTRA $3.50 PER MONTH just to fund the damaging anti-carbon war unleashed by Gore, Mann et al. I wonder how many other uninformed utility-bill payers like me were unaware of this EnviroTax Rip-off.
Andrew H says:
May 30, 2011 at 12:19 pm
Not true. A group of random proxies will be dominated if there is a cohesive group of similar outliers. In this case, what we have is a lot of proxies that mostly do nothing except cancel each other out. So in any kind of averaging, whether you use sophisticated weighting techniques or not, once those have cancelled out what’s left is the cohesive (but false) signal of the Graybill bristlecone and Tiljander and Tornetrask proxies.
What I’m saying is that Mann didn’t “ignore” those other proxies, because there is no need to ignore them. They just cancel out overall, leaving the Graybill etc. data to dominate the landscape. Once that stack of proxies is chosen, the die is cast, and even a simple average of all of the proxies will show a hockeystick.
w.
bob paglee says:
May 30, 2011 at 12:31 pm
Google “Tiljander site:climateaudit.org”, there’s heaps of backstory, I’ve only touched the surface. Mann not only used Tiljander upside-down once. Unbelievably, some of Mann’s co-authors re-used it upside-down in a subsequent paper after being informed of it … talk about unending hubris.
Anyhow, Steve McIntyre has the whole saga over at climateaudit. I highly recommend it.
w.
Great work. Another great contribution to the defense of science. Thanks. Too bad that defense of science is pretty much limited to WUWT, ClimateAudit, Montford’s blog and a few others.
It was not until the Tiljander episode that I fully understood the lengths that the team were willing to go to fudge the record.
A mistake in science, particularly in a method so dependent on programming and messy data, is not unusual and is forgivable. The team’s treatment of Steve McIntyre was bad, but was not yet in my mind unforgivable – egos being what they are.
But to goof up so fundamentally on a dataset whose collectors warned of its contamination and then to dissemble the way the team did on Tiljander was what convinced me that something other than good faith science was at work and tempted me to use the “f” word to describe their actions. Noting else could explain their actions.
I wonder when the truth will finally dawn on politicians that they have been well and truly hoodwinked by the team? Some will likely refuse to see the truth, but how long will it take before the majority get a clue?
We should ask the NHL players if their hockey sticks are made of stripbark pine. It take the best wood for the best Hockey sticks.
Thanks for pointing that out to me Willis, I stand corrected.
I read some time ago that the methodology of Mann’s statistical analysis meant that even telephone numbers inputted from the Yellow Pages at random would produce a hockey stick. Your explanation confirms this?
[REPLY] Steve McIntyre demonstrated this most conclusively. My explanation has nothing to do with that.
The program compares all possible pairs of proxies, and measures their similarity.
How is ‘similarity’ measured in your analysis?
Willis, can you confirm that in your cluster analysis the variables are measurements (ring width, density, etc) for the individual years between 1001 and 1980? I’m assuming you normalized each series to a mean of zero and stdev of one before doing the CA.
Can you speculate on why the SW USA Bristlecones split out into three clusters? Is there some pattern in tree location or lab processing? Or does it really come down to strip-bark specimens alone?
Did they use the data upside down? How come this is not widely known?
Oh, the wonders of modern parsing theory and the software that uses it! I scanned the article but did not notice any mention of what software package was used? BTW, this is a type of analysis that I am pretty familiar with as it is similar to what taxonomists use to produce cladograms.
Thanks for all this tasty meat to chew on.
Here is a sceptics intro to dendrochronology and data keeping.
http://uts.cc.utexas.edu/~wd/courses/373F/notes/lec20den.html
http://scienceblogs.com/aardvarchaeology/2009/06/open_source_dendrochronology.php
Leif Svalgaard
May 30, 2011 at 1:29 pm
How is ‘similarity’ measured in your analysis?
###
Good question. I am assuming wavelet analysis. A simple Haar would probably work, give the proper definition of the normal.
When I first saw the hockey stick alarm bells started to ring. It was completely contrary to everything Hubert Lamb had written in a series of books. H Lamb was the climate scientist responsible for the setting up of climate research at the UEA – he lived in East Anglia. If Mann was right everything known about the last 2 thousand years was wrong – how could Mann have been right. My thanks to Steve McIntyre for providing the evidence to rebut the nonsense science of Mann and his pals
just wondering whether James Annan ever returned to this area?
Willis puts it in a nutshell — much appreciated article.
Very nice explanation. The visuals are really helpful. Took me a while to get what you meant by further left, but it all makes sense now. The further left you drew the fork, the closer the match. It’s not just the fork itself (as I had thought), but ALSO how far to the left it is drawn that represents a closer match.
The graphs next to each group is extremely clear.
BTW, I’m a programmer. What kind of dataset is this? Is it sparse data? Point data? How are different graphs compared? Are their offsets automatically adjusted to match when doing comparisons? What about scale? I’d like to learn more about this. I might be interested in creating some really nice graphs as I have some really good drawing tools I created that can draw pretty much anything.
Oh, and where can I get the data?
The Tiljander screw up is utterly amazing. If you want to see how absurd the Team is, study it over at Climate Audit. In a nutshell, the sediment layers in a lake are correlated with temperature. However, after a certain date, sediments from construction contaminated the record. Qualitatively, looking at the sediment record using scientific knowledge, the sediment record shows massive COOLING after that date. The author knew that the sediment record was worthless after that date. However Mann incorporated this record into his chronology model. The model was “tuned” with modern temperature measurements. So the model used the inverse sign for the correlation coefficients, i.e. the data is “upside down”. Anyhow, mathematically the model glommed on to the massive “signal” which “matched” the slight temperature rise in modern times. The effect was that the MWP was flattened out and you got a hockeystick.
It really is this preposterous. Throw out Tiljander, the one tree in Yamal, and the strip bark trees, and you get a nice peak during the MWP, and a warming in current records up to about 2005.
Clear and useful analysis, Mr. Eschenbach — for those who are inclined to analyze.
But tell me this:
Would any analysis, criticism, logical argument or factual evidence help to persuade and bring around those who firmly believe in their irrational ideology, sacred book or mock-scientific dogma? Or those who derive their livelihood from these lies?
My point is, our most important and immediate task is to find effective practical ways and means — financial, organizational, and legal — to overcome the nascent green faith, to deprive it of political support, to take away its access to public funds, and — which is absolutely necessary! — to see that the most active fraudsters stand trial and go to jail.
Scientific bankruptcy of the green scaremongering is obvious not only to us but to its preachers themselves. The most influential priests of “man-made climate change” scare are smiling when they see us debunking their swindle in our blogs. While we are at it, they do the real thing, making political connections, finding rich sponsors, controlling professional and mainstream magazines and associations, dominating in academic institutions and international organizations, incessantly brainwashing the masses with total impunity.
They have money and power. We have none. Money and power are what we need to extinguish this poisonous source of lies before the whole world becomes one faceless, Chinese-style dictatorship spewing pious propaganda, gagging all dissidents, and keeping the large minority of working people under control by feeding products of their ingenuity and labor to the majority of parasites.
In essence, to fight off green lies, we must radically change the structure of democracy. In its present form, there will be soon no real difference between what we call “democracy” in the United States, and what they mean by “democracy” in Syria, Russia, and China.
I don’t see my comment.
What I try to post it again, I see the “duplicate comment detected” message.
Which is a pity — I spent some time trying to lay out my thoughts clearly.
[Reply: Very sorry about that. The only thing in the spam folder was “penis extender”. I don’t think that was your post. WordPress drops comments occsionally, so it’s best to keep a copy until you see yours posted. ~dbs, mod.]
Very tidy. When you’re good, you are very good.
If a picture (or a diagram) was ever worth a thousand words, it is this one.
As always, way to blow the lid off it, Willis.
Chris
Norfolk, VA, USA
Wilis
With regard to the Ababneh Thesis, as with any PhD dissertation, there is should be an embargo on the use of the material by anyone else for a year or two after it is presented to the examiners by the student. The student has sole right to publish the results during that period. After the end of that period the results are available for others to use so long as proper attribution is made. Has anyone examined the question of when the embargo period is due to end?
It pays to look at the source data. Доверяй, но проверяй!
gnomish said: “Very tidy. When you’re good, you are very good”
Mae West: “When I’m good, I’m good, when I’m bad I’m better”.
Sounds a bit like dubious climate research claims
Willis,
Many thanks for your reply to my comments re presumed upside down use by Mann et al of the Tiljander proxies. I followed your suggestion and found considerable information is available at climateaudit.org. Particularly interesting is the mention there of a grudging acknowledgement contained in a “draft Corrigendum” that they had used the Tiljander proxies upside down, but apparently the “Team” was not convinced. Maybe the horse didn’t like the murky, tainted water so it wouldn’t drink.
But in pursuing the spirit of issuing corrigenda where needed, I must confess to a couple of errors in my original posting. Sorry about my typo — the Tiljander data wasn’t “haplessly compromised”, it was “hopelessly compromised”. Also, on rechecking the news story about Gov. Christie’s proposed dumping of NJ’s destructive RGGI cap and trade, I found that the amount stated in the news story was not $3.50, it was “… $3.24 on average toward RGGI on their utility bills.”
There was no billing period defined in the news story, but since it clearly stated “bills” in plural form, I assumed this meant monthly. After digging up the actual rate involved, I now believe the period should have been stated as “yearly payments” instead of just “bills.” I sincerely regret my unintentional misinformation.
Bob
RE: carol smith: (May 30, 2011 at 1:59 pm)
“When I first saw the hockey stick alarm bells started to ring.”
I second the motion. This (combined with the revelation of the logarithmic nature of carbon dioxide warming) is when CO2 Global Warming jumped the shark for me. At first, I tried to give them the benefit of doubt, but I found too many indications that the Medieval Warm Period and the Little Ice Age were global events. It is too bad that your average news journalist does not seem to understand what this fuss is all about. For many people, these numbers and charts are meaningless–all they see are pictures of smoke spewing into the ‘fragile’ atmosphere.
Great explanation Willis!
Am I right in assuming that if each of the 12 proxy groups was given equal weighting and combined (eg 1/12 each) the resultant average would be a cooling trend, especially with the Tiljander set inverted?
I wonder what makes the first Greybill bristlecone & related pine SW USA group so different, when the two later groups seem to show almost no “warming”?
The Hockey Stick Illusion
The whole sorry saga is dealt with in detail in Andrew Montfords’s book that appears on this site and is available from Amazon.
It explains how the HS shape is entirely dependent on a few defective series, the algorithm devised by Mann literally hunts for HS shapes and Mann’s acrobatic filibustering and denial.
Why note buy a copy and support Bishop Hill.
Paul
Mann Made Global Warming
Another excellent addition to the Willis index. It’s also interesting that if one single tree – YAD061 – was deleted, there would be no alarming chart that Keith Briffa used to fabricate a fictitious hockey stick.
Mann knowingly used a corrupted proxy [Tiljander]. But he had been informed before he published that the Tiljander proxy was no good due to road construction, which had overturned the sediment layer. Mann deliberately used Tiljander’s proxy anyway, because it gave him the coveted hockey stick shape. Is that scientific misconduct, or what?
DBS, thank you, my post appeared.
Sometimes there’s an inexplicable delay, which leads to unnecessary complaints and/or repeats. I understand that this is rather beyond your control.
From the article
How is this comparison made?
Thanks Willis. This was my general feel about the subject, but it helps that you itemized it. I read Ababneh’s paper and saw that the non-strip bark trees showed no hockey stick shape at all. In fact, the data was rather flat. I also remember that McIntyre had found that not all of the samples that Graybill had collected had been archived – making it look like there might have been some cherry picking on Graybill’s part. Graybill’s objective was to show CO2 feeding when he collected those samles. Furthermore, the weighing that Mann did also served to increase the hockey stick shape.
A couple of things that I’m still unclear about. What was Mann’s explanation for using the Tiljander data upside down?
The Misc. Asian tree rings do seem to give a bit of a hockey stick shape. Has anyone looked at those?
Rob R: “Has anyone examined the question of when the embargo period is due to end?”
Ababneh’s paper came out in 2006. It seems like Mann should have both known and had access to it for his 2008 paper. Ababneh shows very clearly that the hockey stick rise at the end is a split bark phenomena. She broke her trees into groups that had gone split bark and those that had not. All the trees that had gone split bark showed and acceleration in tree ring growth. Likely, the parts of the tree that died left more nutrients and structure available for the parts that did not die. And of course core samples were pulled from the living bark.
Ababneh used more trees and did a more complete analysis than Graybill. But the fact that Mann is unwilling to update all his old work by replacing the Graybill data with the Ababneh data shows clearly that Mann has zero interest in producing good science. His entire career is dedicated to his personal and political agenda – science be damned.
The ideological grandfather of the hockey stick is in the 1960 cover article
of Science, 4 November 1960, Vol. 132 #3436 pp. 1291-1295
by von Foerster “Doomsday: Friday 13 November, A.D. 2026”
I was in high school and read Science every week
and vividly remember this population-explosion screed.
And yes, it’s every bit as shoddy as its equally wretched AGW descendents.
The cover has a graph from the article, and thus is the original Hockey Stick.
Another bet: all the ClimateGate conspirators have seen and adored this graph .
Irony: the Doomsday Collision of the NEO asteroid Apophis
(if it Keyholes on its close pass on Friday the 13th April 2029)
will be on Friday the 13th of April 2036.
Willis:
This is the simplest, most clear explanation of the HS phenomena that I have seen.
Hats off to you and keep them coming….
“Jimbo says:
May 30, 2011 at 1:55 pm
Here is a sceptics intro to dendrochronology and data keeping.
http://uts.cc.utexas.edu/~wd/courses/373F/notes/lec20den.html
http://scienceblogs.com/aardvarchaeology/2009/06/open_source_dendrochronology.php”
Jimbo,
Your links rock (as usual – you know a lot about this stuff!). I checked out the second one and reading a comment came up with this link:
http://web.utk.edu/~grissino/
I haven’t yet delved into this site much, but it was mentioned as a good source for dendro. Any comments and insights about the site or about Dr. Henri Grissino-Meyer?
bob paglee says:
May 30, 2011 at 3:03 pm
If it’s any consolation, RGGI’s cost to consumers is totally unclear. Here in New Hampshire, on power producer has come up with estimates of $0.065 cents per month and also $0.36 per month.
From the $10 million “returned” to NH in 2010 and the some 500,000 households in NH, I figure the total impact is $10/year at the current low prices per allowance. (People had hoped for 5-10X the current $1.89.) Even so, the major defense for RGGI in NH has been economic. The program has only been in effect for a few years but the recipients of the funds are already very, very attached to them.
Note – my “total impact” includes what you pay to support power bills to your employer, grocery store, traffic lights, etc.
See more at http://wermenh.com/rggiwatch/finance_notes.html
Leif Svalgaard says:
May 30, 2011 at 1:29 pm
The program compares all possible pairs of proxies, and measures their similarity.
How is ‘similarity’ measured in your analysis?
———————————————————————————
The silence is deafening. Can we have an answer please???
BTW—Fantastic work Willis. You will get a Whistleblower fee from all the money we’ll save from abandoning the CO2 imbargo Industry!! But I’m worried Lief has spotted something in your analysis.
Gary says:
May 30, 2011 at 1:30 pm
Yes to both. One caveat, some data was linearly interpolated by Mann et al. to yearly measurements from decadal measurements.
No clue. In general trees are not good thermometers. In dry zones they can be passable rain gauges, but thermometry is generally beyond their vocal range, with loads of unmeasurable confounding variables.
w.
DesertYote says:
May 30, 2011 at 1:46 pm
You’re welcome. I did the analysis in R, based on the R code provided by a commenter on my earlier thread cited in the opening of the head post.
w.
MrX says:
May 30, 2011 at 2:11 pm
Thanks for asking. I’ve put an update at the end of the head post with a link to the data.
It’s annual data 1001-1980. To compare them I standardized them (set their mean to zero and standard deviation to one). Then you can compare them and average them directly.
The scale is in units of standard deviation. I created the whole graphic of Figure 2 as kind of a kludge, because I don’t speak “R” (the computer language I use) very well. So I made up the dendrogram and each of the individual graphs separately in R, and then screenshot each one. I then assembled them in my graphics program of choice (VectorWorks) and added the lines from each graph to the corresponding cluster and the like.
w.
It’s very inappropriate to associate waterboarding with such tortured data. Ask William F. Buckley what torture is.
What amazes me most in debating AGW enthusiasts is something they don’t seem to comprehend that cannot really be forcefully argued since it’s basically common sense and pure logic: that if a statistical mash up of a bunch of, say, tide gauge records shows a recent surge then that result is meaningless if it relies on a few outliers (or lots of records too short to contain historical trend information) when in fact the vast majority of tide gauge records fail to show any trend change at all, worldwide. If the claimed effect is a sudden global surge in T and sea level, then it’s amazing how they can glibly assert that “it’s global not local, you idiot!” when I ask them why such a huge surge in two variables doesn’t not show long single site records scattered all over the place.
I believe they simply can’t think clearly.
It’s also amazing how they keep pushing hockey sticks while pompously asserting that commenters cannot possibly provide proxy studies that show a hotter MWP. When I link to a hundred or so of them, they twirl back around and claim they are all just “local” even though they are from all over the globe (http://www.co2science.org/data/timemap/mwpmap.html).
In Cook’s book on “denial” he bastardizes the term “cherry picking” to describe the nefarious practice of harping on research papers that fail to support AGW. He writes: “They cherry-pick one contradictory study and they promote it relentlessly.” In other words he has turned Feynman era scientific rigor into something to mock.
He also writes: “Just because there a professor of something denying climate change does not mean it is not true, it just that the professor is in denial. This is why one must make use of the preponderance of evidence in science, the collective view.”
So here we have a group of very vocal AGW supporters who downright reject the very idea that a single result can topple a whole theory. They really do believe that science works by paper counting and academy proclamations rather than according to ideas. Thus there is no reasoning with them using specific results. They describe numerous falsifications of CAGW as merely being “some inconsistencies”.
They are proudly promoting a false view of the very nature of science itself. I wonder how this factor could be better exposed as being a form of corruption? What started for me as climate homework has turned into a psychology puzzle.
-=NikFromNYC=- Ph.D. in Chemistry (Columbia/Harvard)
Rob R says:
May 30, 2011 at 2:49 pm
Dunno, but Malcolm Hughes and the rest of her committee signed off on her thesis in July of 2006.
w.
Tilo Reber says:
May 30, 2011 at 4:36 pm
Hasn’t given one as far as I know.
Of course, Steve McIntyre, who else. More sleight of hand going on there as well.
w.
johnnythelowery says:
May 30, 2011 at 7:05 pm
Y’know, Johnny, I had a lovely afternoon. My sweet wife Ellie told me she wanted to take me somewhere as a surprise. We got in the car, and she drove me to Armstrong Woods Redwood State Park. Despite living in the redwoods and also living nearby, I’d never been there. We went, and it was a living cathedral, a symphony of green. Awesome.
Then we drove over to her dad’s place. Billy’s 82 and effectively blind. I did some work around his place while Ellie read his bills and letters to him and wrote checks. Then we all got in the car and drove about four blocks to the nursing home where Ellie’s mom is. She’s a sweet lady, half her body paralyzed from a stroke. Ellie rubbed some cream on her face. Billy and I stood around and cracked jokes. All in all, it was a lovely afternoon.
Then we came home, and what do I find? … someone’s upset because I haven’t answered a question yet.
In any case, the answer is that the distance measure I used was (1 – absolute(covariance)). Or you could use (1 – absolute(correlation)) and get the same answer. Or 1 – r^2, for that matter.
w.
Willis,
I can’t describe how useful a non-expert like me has found your posting, especially figure 2. It brings so many things together that so far hadn’t quite gelled in my mind. This post has gone into my bookmarks.
The Asian tree rings include Yamal and Jacoby’s Mongolia seris, both used over and over. Briffa’s Yamal series is, oddly, included in the series labeled “Tornetrask”, which isn’t Tornetrask but an average of Tornetrask, Yamal and Taymir – something that is impossible to guess, but if you know the data, you watch for Mannianisms.
From eyeballing the graphs, what stands out to me is that if you throw away the discredited proxies, what you’re left with looks like a bunch of meaningless noise. It’s difficult to see any underlying pattern that might represent “global temperature”.
Is there any reason to believe that any of these proxies are up to the job?
Another one out of the park. If Willis doesn’t yet hold the all-time home run record, he will soon. 🙂
This is the clearest and most concise presentation of the issue I have seen. Very well put together.
I was aware of all the issues but having it on one sheet with the mini plots on the left makes it instantly assimilable and very clear how much depends on use of unsuitable bristlecone and inverted Tiljander including the damaged part of the record.
It would be interesting to see if any kind of signal can be dug out of all this noise once the bristlecone is removed and Tiljander is cropped to conserve the valid data and used the right way up !
It’s hard to see with that level of s/n ratio but it looks like MWP and LIA may well emerge from the mud.
Has no-one ever done this?
Re
James Evans says:
May 30, 2011 at 11:19 pm
“Is there any reason to believe that any of these proxies are up to the job?”
No.
There’s some theoretical stuff, involving Oxygen isotopes, but sometimes these are cited as “evidence” of increased precipitation, othertimes as temperature proxies.
These isotopes are found in both ice cores and speliotherms (stalagtites & stalagmites & their kin).
The idea of lake sediments, is that in warmer waters, there’s more plant growth & thus more to decay & form thicker/denser layers of mud.
The concept behind “treemometers”, is that (all other things equal), trees on the polewards extremes of their ranges, will make the most of a warmer & longer summer to put on growth.
Big, nay enormous, holes can be picked in all of these theories!
Re
Alex says:
May 30, 2011 at 1:43 pm
“Did they use the data upside down? How come this is not widely known?”
Yes, they did & for those who’ve read the posts on the subject at “Climate Audit” & Andrew Montford’s book “The Hockey Stick Illusion”, it is well-known.
It’s yet another area, where the inconvenient truth was raised & the incestuous climatatology community closed ranks, either went “La la la, we’re not listening” or denied it.
http://wattsupwiththat.com/2009/11/27/told-ya-so-more-upside-down-mann-in-his-latest-paper/
It is quite obvious that the signal to noise ratio in this tree-ring data is quite low, especially if someone goes out of their way to select noise in preference to the signal.
It is so easy to assume that everyone is aware of the lack of good evidence supporting the CAGW theory that we often forget how many people still believe that it is a true and they have a duty to stop it. (cf. Bill Nye) Even the President recently spoke of forging an international agreement to control carbon emissions.
He says “The sign doesn’t matter.”
So let me get this right–the world is in an uproar, spending billions and billions of dollars all because some ego-saturated would-be “scientist” fudged the data, got himself a cushy way to grab grants by doing it, and can’t even be honest enough about it to say he was wrong? Sheesh–this Mann character is really something. Somebody needs to yank his credentials. He’s one dangerous dude! (The people granting him all that money are just as guilty as Mann, by the way–they should be taken to task too.)
Thanks boss, that seems to take care of that little bit of chicanery.
Thanks for this it’s very insightful, and good timing too as Anthony has just posted a picture of Al Gore scaling a ladder next to the giant stick. Looks like Al could have used a foot stool if it was done right.
Thanks for keeping this afloat Willis. I thought the thorough gutting of this beast by McIntyre was sufficient. The fact that the hockey stick is still propped up seems to prove this point from NikFromNYC:
NikFromNYC says: May 30, 2011 at 7:48 pm […]
So here we have a group of very vocal AGW supporters who downright reject the very idea that a single result can topple a whole theory. They really do believe that science works by paper counting and academy proclamations rather than according to ideas. Thus there is no reasoning with them using specific results. They describe numerous falsifications of CAGW as merely being “some inconsistencies”.
I got a little lost at CA trying to understand all of this, but you laid it out in a very plain, and easy way to understand !!!
Another great post Willis !!!!
to recap why bristlecones are not good to use: the extreme hockey stick shape is found mostly in “strip bark” trees. These are trees that have been damaged on one side by frost, drought, fire or something. The bark on the other side of the trunk starts to grow extra fast to compensate for the lost bark on the damaged side. The extra growth lasts for a century or so and has nothing to do with climate–it is a healing response. The Ababneh thesis showed that if you pick trees that are not damaged, you get no hockey stick shape. No cookies indeed. This is so simple and obvious that even a cave man should be able to understand. Using these trees is like trying to predict running speed using only a population of amputees, without mentioning that fact in the study.
I have just started to dig in to the hockey stick controversy in depth. This was a very helpful summary post for me on Mann’s proxies.
I don’t want to create extra work for you, but it would be very helpful to create a similar analysis for all the proxies used on the spaghetti graphs. I find that Mann’s defenders, when backed into a corner, inevitably try to switch topics to all the other “indpendent” studies that reach the same conclusions as Mann. It would be nice to have a succinct summary chart such as the one you provide here that could demonstrate that they all rely on the same flawed proxies for the hockey stick shapes.
@PaulD
I think you’ll find that the so-called “independent” studies aren’t independent in any important sense of the word. They are all conducted by co-authors of Mann, or by co-authors of his co-authors, use the same defective proxies and largely the same defective statistical methods. They just shuffle things around and hope no one will notice.
@- Willis Eschenbach
I understand you can find inumerable caveats about the dendro-proxy data, it is noisy and u8nreliable over the most recent century. The variance over past centuries does seem to implie a rather flat climate but with big uncertainty/error bars – exactly as the original MBH98 graph.
But in circumstances when one source of data is uncertain the usual response is to look for alternative proxy sources and try and achieve a consilience.
Or at least see if an alternative proxy measure gives a radically different, or largely similar result.
How do climate reconstructions based on all the other paleoclimate proxies found at –
http://www.ncdc.noaa.gov/paleo/data.html
compare?
There have been a fair number of paleoclimate reconstructions, not all are based on tree ring data, but AFAIK none refute the pattern of some past variability with a rapid rise at the end during the last century.
http://www.ncdc.noaa.gov/paleo/recons.html
Tilo Reber asks: ” What was Mann’s explanation for using the Tiljander data upside down?”
The response by Mann that I am aware of is simply this: “The claim that “upside down” data were used is bizarre. Multivariate regression methods are insensitive to the sign of predictors.” I don’t have the link, but Mann published this in response to a published comment by M&M.
This response is completely inadequate. Here is a excellent explanation of the issue that I found in the comments on another blog:
“The sort of multivariate regression techniques that Mann used are effectively data mining: you take a bunch of datasets that you have some vague reason for believing might be proxies for temperature, and then regress them against an instrumental record for some calibration period. This reveals the small number of “proxies” which did in fact correlate well over that period, and you then attempt to reconstruct other periods by assuming that the same datasets are similarly good proxies over other periods, effectively weighting them by their correlation coefficients.”
“Like any data mining approach this is fraught with dangers; in essence you can just pick out a bunch of random noise sequences which happen to correlate by chance. This can be partly guarded against by checking the reconstruction against a verification period, though you have to be extremely careful how you do this, and many criticisms of Mann’s verification statistics have been made.”
“There is, however, a simpler check, which is just to look at the sign of the correlation. If a “proxy” anti-correlates with the instrumental temperature, going down when temperature goes up, then the regression program will give a negative correlation coefficient, and so it contributes to the reconstruction with a negative weight. Nothing wrong with that. However for most plausible proxies it is possible to assign the sign of the correlation coefficient a priori (indeed some people would argue that if you don’t even know the sign a priori, then the chance of something being a genuine proxy rather than just fortuitous noise is low).”
“Now we turn to Tiljander’s sediment data. This data does have a well defined a priori sign, but it turns out that when placed into Mann’s program it comes out with the wrong sign for the correlation coefficient, so that in the reconstructions it is turned upside down. Why did this happen? Because Mann’s correlation is run against the modern period, where Tiljander’s data is badly contaminated by the effects of bridge building, and this modern contamination correlates well with temperature IF you turn the dataset upside down!”
“So yes, multivariate regression methods are insensitive to the sign of the predictors, but no this doesn’t mean that it can’t end up using datasets “upside down”; in the case of Tiljander’s data it can and it did.” ” http://andyrussell.wordpress.com/2010/06/15/the-hockey-stick-evolution/#comment-540
From me: This point seems obvious. But go over the and read the comments at climateaudit.org on this very issue and read some of the comments on some of the “team” blogs. It is absolutely amazing how confused some scientists are on this elementary point and it is amazing that Mann and his team won’t concede this point.
“you can get a hockeystick if you waterboard this data long enough”
🙂
A skeptical view of the “hockey stick”, written by McShane and Wyner, is now available in hard copy, with discussion and rejoinder, in the Annals of Applied Statistics, Vol 5, Number 1, dated March 2011, pages 5-123. There is an expanded rejoinder along with lots of data and code from the discussants in the supplemental online material through the Annals of Applied Statistics web page at the Institute of Mathematical Statistics web page: http://www.imstat.org.
Most of this was available on the internet before now, but I think it is worthwhile to read the hard copy version.
Discussants included Schmidt, Mann and Rutherford; and McIntyre and McKitrick; in all, there were 13 papers by discussants, plus the original and rejoinder by M&W. Like Willis today, and others here and there, M&W point to the dependence of the hockey stick shape on a selected subset of the data. Schmidt et al defend the selection, as you’d expect.
Willis,
I think that you should write up today’s comment for a professional journal. I think you have presented a nice clear case.
Willis, thanks for the charts and overview of upside down Tiljander. They clearly show that what was going on here certainly wasn’t science.
Willis, I don’t know quite how you manage to keep producing so many easy-to-read, easy-to-understand articles, but many thanks for another one. Your figure 2 is superb: take out the two known dodgy datasets and the hockey stick evaporates. Once again, many thanks.
Alexander Feht – I completely agree with you. We need a popular, public face to stand up for real science, before the vacuous “celebrities” who regularly trumpet AGW nonsense completely pollute the public’s perception of science. Unfortunately, the fact that no-one springs to mind makes me, too, wonder whether the popular perception of “science” has been so contaminated already as to appear “settled” – at least, for long enough for the shower playing for global power to make their putsch. The next few years are going to be “interesting”, if none too pleasant.
first drown it in holy water , then shoot it with a silver bullet, then drive an oak stake thru its heart, then behead it and finally burn the head and body in the fires of Mount Doom … then maybe it stays down … maybe … also, if you find the ring of power, also drop it in the fires of Mt. Doom just to be sure …
“The discussion of the 1998 Mann “Hockeystick” seems like it will never die.”
… says Willis in the opening sentence. That is a little bit artful & coy, since WUT
and CA are the main agents keeping this discussion alive at the detriment of a
broader, updated perspective on climate reconstruction studies.
Of course I can see the difficulty for sceptics here: the reconstructions generally
reproduce the MWP and LIA periods, which you are fond of, but at the same
the recent warming peak invariably shows up and most often, it already exceeds
the MWP peak. With (a) warm years piling up recently, (b) new proxy studies
being published all the time, your battle against the Hockey Stick is doomed
to fail.
The bristlecone data is erroneous? Exclude it, no major difference.
In fact, exclude all tree ring data? No major difference, now when other proxy
data is increasingly available.
Exclude also the Tillander data? No major difference.
Mikael Pihlström says:
May 31, 2011 at 11:29 am
Check the blogs. I actually said this based on a discussion of M2008 on Judith Curry’s blog, but this question has been (and is being) discussed on a variety of sites. The problem, of course, is that Mann (and folks like you) keep claiming that there were no problems in Mann’s work. If Mann and y’all would simply own up to the egregious errors in his work, the issues would go away … but until then, they will continue to be brought up by folks around the planet. Sorry, but that’s what happens when you claim that errors are correct … it makes them persist.
And a “broader, updated perspective”? What does that have to do with whether M2008 stacked the decks by the choice of proxies? Whenever someone points out problems with Mann’s work, fools always jump up and say “But that doesn’t matter, we’ve moved on to new studies now” or that we have a “broader, updated perspective” now. So what?
Sorry, but Mann’s work is good or bad depending on what he did, not on what new studies might show. And in this case, I can see why you’d like us to look somewhere else, anywhere else … because his work is bad. Really bad. Using proxies upside-down bad. Using Graybill bristlecones bad.
Now, I know you’d much rather we look at something else, but the new “broader, updated perspective” is mostly a repetition of Mann’s work, including the errors. Including the non-recommended proxies like the bristlecones. Heck, even including non-recommended proxies upside-down. And definitely including other bogus proxies like the Polar Urals and Tornetrask. So no, you can’t get out of it by saying that Mann is so yesterday and you’ve moved on.
I also like your dual pronged approach:
• It doesn’t matter that Mann’s work is wrong, because it is no longer relevant as it has been superceded (since 2008?) by newer (although uncited) studies, and,
• Mann’s work is right.
Hmmm … do you see a conflict there? Pick one or the other, Mikael, or you’ll get the splits from riding two horses.
Cite? I love the hand waving and the claims of “new studies”, but without citations that’s just you flapping your lips and hoping people won’t notice the lack of facts. And “warm years piling up recently”? See Phil Jones on how there’s been no statistically significant temperature increase in fifteen years.
Again, I love the handwaving … but some citations would be nice. Michael Mann has made a similar claim, but his graphs show that his claim is just handwaving as well.
And “now when other proxy data is increasingly available”? What does that have to do with the use of bogus proxies in Mann 2008?
Finally, you claim that the “recent warming peak invariably shows up” … to be sure, if you “hide the decline”, you get an incline. You do understand that they needed “Mann’s Nature trick” in order to hide the fact that recent warming didn’t “invariably” show up as you claim?
Or perhaps you don’t understand that. If so, you also may not be aware that Mann’s method finds hockeysticks in random red noise … if you know what that is. See e.g. Principal Components applied to Red Noise. So the Mann himself finding yet another “hockeystick” with a “recent warming peak”, that don’t impress me much, although I can see why uninformed people might think it is important. But since we can get that result from random red noise using Mann’s method, it’s meaningless.
In any case, Mikael, so far in your post you have provided erroneous claims and handwaving … not a good start. There’s further reading for you about the proxies and how Mann can make a hockeystick by proxy selection in M2008 here and here and here and here and here, if you are actually interested in the proxy issues. Yes, you are correct, if you put a bunch of bogus proxies in, you can remove a subset of the bad proxies and still find a hockeystick. You seem to think that means something …
Finally, tree ring width sucks as a proxy for temperature. There’s a good explanation of why (in the process of explaining a much more accurate method for estimating ring width from the variables that control it) here (PDF poster about the Vaganov/Shaskin model of tree ring growth).
If you actually are interested in the proxy issues, come back and tell us how all of those analyses are wrong, with real facts and citations and leaving out the handwaving.
All the best,
w.
Steve C says:
May 31, 2011 at 10:50 am (Edit)
Thanks, Steve. Actually, there’s more than two dodgy datasets in the group. See the links in my post to Mikael immediately above for a non-exhaustive list. Also Steve McIntyre pointed out a few more above.
w.
PaulD says:
May 31, 2011 at 8:09 am
Paul D, thanks for a very clear explanation of the issues. Mikael (above) thinks that it is sites like WUWT and CA that keep this issue alive. What keeps it alive is that Mann and folks like Mikael won’t concede even the most obvious of errors, for example that Mann used Tiljander a) in defiance of the instructions of the original authors not to use the whole dataset for reconstructions, and b) upside-down.
There’s a report of the original finding of upside-down use of Tiljander here, and a good discussion of related issues here.
w.
PS – Relevant citations. Mann’s comment, that the claim that Tiljander was used upside-down is “bizarre”, was in reply to McIntyre and McKitrick’s rebuttal in PNAS. Mann’s reply is here.
Willis:
I did not have the background to figure out use of R readily when I once tried or else I’d look into using this type of analysis also on long running (century old) tide gauge records, of which there are dozens. They are here: http://www.psmsl.org/data/obtaining/. I do believe the resulting analysis would be highly damning to claims of recent surges in sea level since very much like these proxies the vast majority of records show no trend change at all, at least by eye. They are, on average, a characterized by a lack of trend change on the decadal scale, which is not something you find so readily in single site thermometer records, so sea level in my mind becomes a potentially much better counter to one of the two central tenants of AGW: that both T and and sea are suddenly surging.
-=NikFromNYC=-
NikFromNYC says:
May 31, 2011 at 2:01 pm
Thanks, Nik. I don’t think that cluster analysis of tidal gauges would reveal what you think it might. The problem is that tides are a basically non-repeating series, which kinda repeats every eighteen years or so, and pretty much repeats every fifty two years or so, but which contains even longer cycles than that.
These cycles overwhelm everything, so just getting a trend from tidal data is a difficult and very long-term exercise. You kind of have to work it backwards. You use the data to take the best estimate of the “tides of the moon”, that is to say, the size of the effect of each of the fifty or so cyclical earth-moon-sun interactions (apogee, perigee, phase, declination, the list is long) on the local tide.
Then you remove those cyclical influences, and what’s left is your best estimate of the trend … not a pretty way to get a number, but it’s the best we have. The ugly reality is that there is absolutely no theoretical way to determine the tide at a random point. We can only do it as a result of a long, long series of observations.
In addition, the tide at a given location is a function of where it is on the earth (tides near the poles tend to be larger), the nature of the oceanic basin, and any land features (bays, lagoons, etc).
For example, most places have either one high and one low tide per day, or two high and two low tides per day. The Solomon Islands, on the other hand, has one high and low tide for part of the year, and has two highs and lows for part of the year.
So overall I don’t think cluster analysis would be much help there. All you would end up saying is “well, the tides in the Solomons are most like the tides in X”, but that doesn’t help much.
w.
Mikael Pihlström.
All you need to produce a flat shaft is some proxy that has a blade.
1. BCP
2. Tiljander
3. yamal.
So, its easy to drop BCP and get a flat shafted hockey stick
easy to drop Tiljander, easy to drop yamal.
Thats been the trick. drop one keep the others. drop 2 keep one.
pea thimble.
if you understood what the underlying methods did to supress variability in the shafts you’d understand better. read Jeff id. or better run his code
trees are a very poor proxies for temperature. when you look at water content/sun/food/temp the combinations and variables can lead you astray very quickly. especially if you have no records or observations to verify the findings.
makes one wonder what Mann was thinking when he used them. a questionable source and hard to verify… that’s the answer…. hide the data and hard to replicate.. where have i heard that process before?
Willis: “There’s a report of the original finding of upside-down use of Tiljander here, and a good discussion of related issues here. ”
Okay, I think I get it. Basically, Mann’s software picked the sign. Since upside down Tijander data would coorelate to other data for the last 100 years, Mann’s software simply decided for itself how the data should be interpreted – ignoring the real world interpretation. The odd thing about this is that the software would have to decide that it didn’t care that the coorelation for the MWP and LIA was destroyed by doing such a sign inversion. Mann probably used the results without checking since it gave him what he wanted. Then, after his error was exposed, Mann had to make a decision, lie or acknowledge that he had done something really stupid.
As always, Mann choose to lie. If I’m interpreting this correctly, what he said was, “using the data with the sign as I have used it causes the data to coorelate with other data around the world, so – my sign is correct.” Basically, he called Tiljander a fool who didn’t understand the physical interpretation of his own data. He ignored the inverted correlation that his interpretation caused for the MWP and LIA, and he ignored the fact that his misinterpreted hockey blade actually had the shape that it had due to man made construction projects screwing up the data for the last 80 years. And he purposely ignored these things even though they were pointed out to him just so that he could make the claim involved in his lie.
Going one step futher, Gavin is not so stupid that he did not realize that Mann was lying. And yet he helped to prop up Mann’s lie. I don’t know how else to say this, but how is it possible for Realclimate to be considered anything but a propaganda organization for a warmist mafia.
Come on Leif, get off the fence – say something. This issue looks to be 100% clear cut to me. Can you think of any defense for Mann’s actions?
The AGW crowd keeps telling us that Mann’s results are supported by “independent” studies. OK, when will someone list and review those “independent” studies? I’m available to assist in any reviews of these “independent” studies.
steven mosher says:
May 31, 2011 at 8:15 pm
Exactly. Since most of the other proxies basically average each other out, adding a few hockeystick shaped proxies dominates the entire thing. So they pull out some and not others and say see, our hockeystick signal is robust.
My analysis, however, shows how few proxies from how few places actually have a hockeystick shape. The asian tree ring series, the bristlecone and stripbark pines, and Tiljander.
This is not to say that there are not problems, in some cases large problems, with other individual proxies. But those few groups are the source of the hockeystick.
The key is in the picking of the proxies. Mann is always trying out new techniques for extracting the data, but the techniques are not the point, that’s all misdirection. You could use plain averaging and get a hockeystick, as long as you have some hockeystick records in the data. Doesn’t take too many, particularly if your algorithm weights them heavily compared to the others …
w.
Willis Eschenbach says:
May 31, 2011 at 11:24 pm
steven mosher says:
May 31, 2011 at 8:15 pm
“So, its easy to drop BCP and get a flat shafted hockey stick
easy to drop Tiljander, easy to drop yamal.
Thats been the trick. drop one keep the others. drop 2 keep one.”
OK. It is principally correct to watch out for such easy tricks. But, on the other
hand, it is also very easy to post-facto identify anything resembling a HS shape and dismiss those datasets with something less than impartiality. And that is my main point: with the increasing basic evidence available the sceptic tenet that all
HS-resembling datasets are corrupt/misinterpreted/falsified is faring badly.
Willis, you are in error when you say the computational method of Mann et al flipped over Tiljander. The software does not do any flipping of Tiljander proxies. The error was that Mann should have manually flipped Tiljander before using it, to make warm point upwards. Then after this flip, the software would have dropped it for being uncorrelated.
Mikael Pihlström says
“And that is my main point: with the increasing basic evidence available the sceptic tenet that all
HS-resembling datasets are corrupt/misinterpreted/falsified is faring badly.”
As someone who is actually interested in understanding this issue and getting to the bottom of it, I would appreciate a link or a citation that would support this point. I would actually like to investigate whether it is true. When I have evaluated similar claims from other websites I have found such claims to be unsupported.
My own reading leads to me to a different conclusion: There are a few basic proxy series that are responsible for the blade of the hockey stick in all of the supposedly “independent” reconstruction. When those proxies are examined, there are sound physical reasons to conclude that they are not good temperature proxies. (e.g. the Tiljander series, the strip bark series).
Nothing that I have read would cause me to reach the conclusion that, “the sceptic tenet that all HS-resembling datasets are corrupt/misinterpreted/falsified is faring badly” I am willing to be persuaded otherwise, but you will need to point me to some evidence.
Mikael Pihlström: “But, on the other hand, it is also very easy to post-facto identify anything resembling a HS shape and dismiss those datasets with something less than impartiality.”
Since the way in which you make your living is dependent upon Mann and the other warmists being right, I don’t think you have much room to talk about impartiality.
Mikael Pihlström: “And that is my main point: with the increasing basic evidence available the sceptic tenet that all HS-resembling datasets are corrupt/misinterpreted/falsified is faring badly.”
No, that is untrue. First of all, there has never been a serious debate about temperature increase in the last century. The debate has been all about that temperature increase being “unprecedented” within the last 2000 years. In other words, it has been about the flat shaft of the hockey stick. And with regard to that the “increasing basic evidence” is that there was a substantial MWP and LIA. And that evidence says that the proxy MWP was as warm as the proxy data for today. So it is the assertion that today’s climate is unprecedented that is fairing badly, because the hockey stick is, is fact, wrong.
Mann’s flipping of the Tiljander data also turned the MWP and LIA upside down and thereby contributed to making the shaft flatter.
What is interesting Mikael, is that you talk about impartiality, but you don’t seem to care how corrupt Mann is in the way that he does his science. All that you seem to care about is being able to declare victory for your agenda at the end.
Here’s something interesting, and slightly off-topic-
I was going to try to locate one of the Graybill Bristlecones during an upcoming fishing trip to the Eastern Sierras. CA531 (Graybill-Onion Valley) seems to be an ideal candidate. Long/Lat and elevation can be found here:
http://www.ncdc.noaa.gov/paleo/metadata/noaa-tree-3393.html
North: 36.77 * South: 36.77
West: -118.35 * East: -118.35
Altitude: 2865 m
When I checked the correlation stats I came up with entirely different coordinates:
ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/measurements/correlation-stats/ca531.txt
Latitude : 3546 N
Longitude : 11821 W
Elevation : 2865 M (actual elevation is less than 2000 meters)
This location is in the Sequoia Nat. Forest, near Bright Star Canyon; 100 miles south of Onion Valley and approx. 800 meters lower in elevation. Checked the entire Graybill database for a Bristlecone located at 35.46N/118.21W. Nothing.
How can the same tree be located 100 miles south of Onion Valley?
I always knew Mann-made global warming was real! This further confirms it!
Mikael Pihlström says:
June 1, 2011 at 4:00 am
No, Mikael, that’s not your main point. That’s the point that remains after your other points have been demolished. You had a bunch of other main points before, points that were as lacking of substance and substantiation as this latest one.
Because once again you’re just flapping your lips. CITATIONS, bro’. Citations are your friend.
For example, you say:
“Increasing basic evidence”???
That’s meaningless, Mikael, without some kind of citations. But I’ll bite.
What “increasing basic evidence” is showing that the bristlecones (or the asian tree rings or the Tiljander data) are suddenly somehow correct?
What “HS-resembling datasets” are you claiming are NOT corrupt under the rubric of “increasing basic evidence”? Names, Mikael, locations, specifics, that’s what is necessary. Not your unsubstantiated vague fantasies about some unspecified new “basic evidence”.
Now, please don’t just come back and give us more bafflegab. Your lack of citations has been commented on before. And because of your unwillingness to back your claims up with facts despite repeated requests, at this point your word means nothing. You’ve destroyed your credibility entirely through your extravagant unscientific claims and your obstinate refusal to provide even the merest scrap of evidence for a single one of your claims.
If you come back again for a third time in the same manner, with nothing but your extravagant un-cited claims in one hand and your Johnson in your other hand, I’m not going to answer. I’ll just point and laugh.
w.
Duke C. says:
June 1, 2011 at 9:11 am
Duke, perhaps you should ask that question of Steve McIntyre over at ClimateAudit. He’s done some field investigation of Graybill trees to try to verify the “Starbucks Hypothesis“, and knows more about the subject (and perhaps how you might document the tree) than anyone I know.
w.
>>
Ric Werme says:
May 30, 2011 at 6:34 pm
If it’s any consolation, RGGI’s cost to consumers is totally unclear. Here in New Hampshire, on[e] power producer has come up with estimates of $0.065 cents per month and also $0.36 per month.
<<
Maybe it’s because they’re using the frequency version of Wien’s displacement law for one estimate and the wavelength version of Wien’s displacement law for the other estimate.
/sarc
Jim
Mike N “Willis, you are in error when you say the computational method of Mann et al flipped over Tiljander. The software does not do any flipping of Tiljander proxies.”
Mike, I made the same mistake. Let’s first go back to what Mann said about the upside down data.
Mann: “The claim that ‘‘upside down’ data were used is bizarre. Multivariate regression methods are insensitive to the sign of predictors. Screening, when used, employed one-sided tests only when a definite sign could be a priori reasoned on physical grounds. Potential nonclimatic influences on the Tiljander and other proxies were discussed in the SI, which showed that none of our central conclusions relied on their use.”
And now let’s look at what Steve M said about Mann’s statement.
Steve M. “These comments are either unresponsive to the observation that the Tiljander sediments were used upside down or untrue. Multivariate methods are indeed insensitive to the sign of the predictors. However, if there is a spurious correlation between temperature and sediment from bridge building and cultivation, then Mannomatic methods will seize on this spurious relationship and interpret the Tiljander sediments upside down, as we observed.”
It was from this that I concluded that Mann’s algorithm was at fault. Can you give us more details about how you think that Mann got the sign backwards. Did he just start with an inverted physical interpretation. And what do you make of his incoherent argument about gettting it right?
One more thing, what is Mann talking about when he says, “a priori reasoned on physical grounds”. A priori knowledge is knowledge which can be know to be true or known to be false without experiential reference to the physical world. So the phrase basically makes no sense. I think Mann loves to throw out obtuse explanations, and then claim that he has addressed an issue when it comes up by reference to those explanations, regardless of how illogical the explanations are.
Wow! .. Beautiful work Willis! .. thank you!
I’m on board with Squidly. Willis is the master of clear, objective thinking.
And thanks to Tilo Reber. That needed to be said. The day that Michael Mann is in an adversarial setting is the day that Mann will be destroyed, because he will no longer be able to obfuscate. Mann is nothing more than a climate charlatan.
PaulD says:
June 1, 2011 at 7:16 am
Mikael Pihlström says
“And that is my main point: with the increasing basic evidence available the sceptic tenet that allHS-resembling datasets are corrupt/misinterpreted/falsified is faring badly.”
As someone who is actually interested in understanding this issue and getting to the bottom of it, I would appreciate a link or a citation that would support this point.
Willis Eschenbach says:
June 1, 2011 at 10:41 am
What “HS-resembling datasets” are you claiming are NOT corrupt under the
rubric of “increasing basic evidence”? Names, Mikael, locations, specifics, that’s
what is necessary. Not your unsubstantiated vague fantasies about some unspecified new “basic evidence”.
————————————–
1.
Twentieth century warming in deep waters of the Gulf of St. Lawrence: A unique feature of the last millennium.
http://www.agu.org/pubs/crossref/2010/2010GL044771.shtml
2.
Ammonium concentration in ice cores: A new proxy for regional temperature reconstruction?
http://www.agu.org/pubs/crossref/2010/2009JD012603.shtml
“For the time period from about 1050 to 1300 AD, our reconstruction shows relatively warm conditions that are followed by cooler conditions from the 15th
to the 18th century, when temperatures dropped by up to 0.6°C below the 1961–1990 average. The last decades of the past millennium are characterized
again by warm temperatures that seem to be unprecedented in the context of
the last ∼1600 years.” [in Bolivia]
3.
Recent Warming Reverses Long-Term Arctic Cooling
http://www.washingtonpost.com/wp-dyn/content/article/2009/09/03/AR2009090302199.html?hpid=artslot
The temperature history of the first millennium C.E. is sparsely documented, especially in the Arctic. We
present a synthesis of decadally resolved proxy temperature records from ‘
poleward of 60°N coveringthe past 2000 years, which indicates that a pervasive cooling in progress 2000 years ago continued through the Middle Ages and into
the Little Ice Age. A 2000-year transient climate simulation with the
Community Climate System Model shows the same temperature sensitivity to changes in insolation as does
our proxy reconstruction, supporting the inference that this long-term trend
was caused by the steady orbitally driven reduction in summer insolation.
The cooling trend was reversed during the 20th century, withfour of the five
warmest decades of our 2000-year-long reconstruction occurring between
1950 and 2000.
4.
A multi-proxy paleolimnological reconstruction of Holocene climate conditions
in the Great Basin, United States osu.academia.edu/ScottReinemann/Papers
“Subfossil chironomid analysis indicates that Stella Lake was characterized by a warm, middle Holocene, followed by a cool “Neoglacial” period, with the last two millennia characterized by a return to warmer conditions.” [The recent warming clearly exceeds the MWP, but there is also a peak 1300 y ago]
5.
Summer Temperature Variations in the European Alps, a.d. 755–2004
Ulf Büntgen, David C. Frank, Daniel Nievergelt, and Jan Esper, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.
http://journals.ametsoc.org/doi/full/10.1175/JCLI3917.1
Annually resolved summer temperatures for the European Alps are described.
The reconstruction covers the a.d. 755–2004 period and is based on 180 recent
and historic larch [Larix decidua Mill.] density series. The reconstruction indicates positive temperatures in the tenth and thirteenth century that resemble twentieth-century conditions, and are separated by a prolonged cooling from 1350 to 1700.
Six of the 10 warmest decades over the 755–2004 period are recorded in the twentieth century.. The record captures the full range of past European
temperature variability, that is, the extreme years 1816 and 2003, warmth
during medieval and recent times, and cold in between.
6.
Recent unprecedented tree-ring growth in bristlecone pine at the highest
elevations and possible causes.
Salzer MW (Salzer, Matthew W.)1, Hughes MK (Hughes, Malcolm K.)1, Bunn AG (Bunn, Andrew G.)2, Kipfmueller KF (Kipfmueller, Kurt F.)3
http://www.pnas.org/content/early/2009/11/13/0903029106
Great Basin bristlecone pine (Pinus longaeva) at 3 sites in western North America near the upper elevation limit of tree growth showed ring growth in the second
half of the 20th century that was greater than during any other 50-year period
in the last 3,700 years. The high growth is not overestimated because of standardization techniques, and it is unlikely that it is a result of a change in tree growth form or that it is predominantly caused by CO2 fertilization. Increasing temperature at high elevations is likely a prominent factor in the modern unprecedented level of growth for Pinus longaeva at these sites.
My conclusions:
We don’t have to rely on tree rings; other proxies are increasingly available.
There are new tree ring sets, admittingly there is large variation in signals
E-g. the bristelcone is not generally disqualified because the sceptics say so
Mikael Pihlstrom: ” ”
So I looked as some of your papers.
“2. Ammonium concentration in ice cores: A new proxy for regional temperature reconstruction?”
Here is the actual paper for that:
http://www.leif.org/EOS/2009JD012603.pdf
And it says:
“Relatively warm temperatures during the first centuries of the past millennium and subsequent cold conditions from the 15th to the 18th century suggest that the MWP and the LIA are not confined to high northern latitudes and also have a tropical signature.”
So, for years the warmers have been claiming that the LIA and MWP were regional phenomena. Hopefully we can put that lie to rest. Now, it you look at the temperature chart that they gave you will see that A. It doesn’t look like a hockey stick. B. There is nothing alarming about it. C. When they use the term “unprecedented” to mean “just a little bit more” they are going off the reservation.
“3. Recent Warming Reverses Long-Term Arctic Cooling”
When I check your link I get a picture from a newspaper of some greenpeace guys standing on an iceberg. You are going to have to do better than that.
Your number four has no source, no link, no anything. You are really going to have to do better than that.
“5. Summer Temperature Variations in the European Alps,”
So here is the link for the crucial chart from that paper. Again, no hockey stick; nothing to be alarmed about; and the twentieth century does not look warmer than the MWP.
http://journals.ametsoc.org/na101/home/literatum/publisher/ams/journals/content/clim/2006/15200442-19.21/jcli3917.1/production/images/large/i1520-0442-19-21-5606-f02.jpeg
And they also provide a solar activity chart that you can compare to three global reconstructions at the bottom. Very interesting, don’t you think. Also, if you look at those global reconstructions you will see one where the MWP was slightly warmer, one where it was slightly cooler, and one where it was about the same. So again, the term “unprecedented” is simply political hyperbole.
http://journals.ametsoc.org/na101/home/literatum/publisher/ams/journals/content/clim/2006/15200442-19.21/jcli3917.1/production/images/large/i1520-0442-19-21-5606-f07.jpeg
“6. Recent unprecedented tree-ring growth in bristlecone pine at the highest elevations and possible causes.”
http://www.pnas.org/content/early/2009/11/13/0903029106
They say:
“The high growth is not overestimated because of standardization techniques, and it is unlikely that it is a result of a change in tree growth form or that it is predominantly caused by CO2 fertilization.”
How do they know that CO2 fertilization is not a factor?
And they also say:
” The growth surge has occurred only in a limited elevational band within ≈150 m of upper treeline”
So they found that this occured only in a band of trees that were 150 meters from the treeline. ROFL. Talk about cherry picked data. If you look at their chart of ring width versus instrument temperature from 1900 the correlation looks good for about 7 years from 93 to 2000. And it looks very bad for the 33 years from 1960 to 1993. Before 1960 it is only so, so.
Here is their 4000 year chart:
http://www.pnas.org/content/106/48/20348/F2.expansion.html
First of all, the last 2000 years don’t look like any other reconstructions. And they have a growth period about 3700 years ago that closely matches that of today – except today we have CO2 fertilization.
This looks to me to be an amplified proxy. The growing period of that last 150 meters is so small that a tiny change in temperature will greatly increase it’s length as a percentage of the whole. Also, looking at the time period for that final spike at the end ( 7 years ), this may well be nothing more than a regional tick with little value for global proxy analysis.
I think that you have proven with your own samples that in the arena of proxy reconstructions, nothing unusual is happening today, and that there is no hockey stick shape to be found except when it is Mann made.
Thanks for your help.
Mikael Pihlström says:
June 2, 2011 at 5:22 am
My friend, you are totally funny, although you likely don’t appreciate that. The authors of the paper you recommend (above) had to issue a correction to Science magazine, generally regarded as an admission of serious failure. And why did they have to do that?
Well, because they had used the Tiljander proxies upside down. Again. Note that this made the third time, as Mann had previously used them upside down twice. And they also used three other proxies upside down.
Ooops … the paper you recommend as so much improved makes the same stupid mistake FOR THE THIRD TIME!
Of course the authors claim that it makes no difference to their reconstruction … now hang on. There’s 22 proxies in their network. They had used four of them upside down. When they turned them over it made no difference.
What kind of funky analysis is it where turning over almost 20% of their proxies makes no difference?
In addition, the reconstruction contains three very shonky tree ring collections of Keith Briffa, one of the un-indicted co-conspirators in Climategate and a co-author of the study. These three proxies (Taimyr, Fennoscandia, and Yamal) have been shown to have huge problems, including the fact that Briffa hasn’t fully archived them … bad Briffa, no cookies … but the team just keeps recycling them.
So no, that study is no evidence for your side at all. It’s actually evidence for my side, evidence that the Mann/Briffa/Amman/Bradley/Hughes axis re-uses known bad proxies because that’s how they can get hockeysticks.
Finally, the study has a common problem with many of these types of studies in that there are no ex ante criteria for proxy selection. As I’ve shown above, if you pick the right proxies you can get a hockeystick by simple averaging. So ex ante selection criteria are critical for this kind of analysis. But the study you recommend has no such criteria.
w.
Here is some more detail on the sediment records from the bottom of Lake Korttajarvi, Finland, that Mia Tiljander and her colleagues analyzed. These make up the Tiljander data set — I no longer think they should be called “proxies”. (I’m writing this from memory, so caveat lector: minor errors could have slipped in. See my blog for details, starting with this post.)
In their publications (listed here), Tiljander et al describe recovering cores from the lake bed. Their key feature is that each year forms a distinct layer (varve), because of seasonal variations in the material that settles out of the lake water. So, starting from the present, one can count year-by-year back to 1000 B.C. or so.
Tiljander et al measured the following properties of each varve (annual deposit):
* its thickness (millimeters)
* the effective thickness of the inorganic (mineral) component (millimeters)
* its transparency to X-Rays (arbitrary units)
Tiljander et al then deduced the contribution from organic matter to each varve by this formula:
(Organic effective thickness in mm) = (Thickness in mm) – (Inorganic effective thickness in mm)
These four data series were deposited in data archives. As used in Mann08, the three “thickness” series were transformed by taking their natural log — a common procedure in the field, I believe.
Mann08 employed these series as temperature proxies. (See Figure 1, the cluster dendrogram in the body of the main post, Figure 1. Similarly, see Figure S8 of Mann08’s Supporting Information.):
* xraydenseave — X-Ray Density (arbitrary units)
* lightsum — Inorganic matter (ln of derived thickness in mm)
* thicknessmm — Varve thickness (ln of measured thickness in mm)
* darksum — Organic matter (ln of calculated thickness in mm)
IIRC, xraydenseave did not pass Mann08’s Screening Procedure, and was not used in the paper’s paleotemperature reconstructions. The other three series did, and were.
In their 2003 paper, Tiljander et al proposed interpretations for XRD, lightsum, and darksum — but not for total varve thickness. In all cases, they cautioned that the varves were progressively contaminated from about 1720 through the end of the 20th century by local activities such as farming, lake eutrophication, and road construction.
Tiljander et al (2003) interpretation
* xraydenseave — Pre-1720 only: higher density means colder
* lightsum — Pre-1720 only: thicker means colder, wetter winters
* thicknessmm — [No interpretation offered]
* darksum — Pre-1720 only: thicker means warmer summers
Mann et al (2008) usage
* xraydenseave — Entire series: higher density means warmer
* lightsum — Entire series: thicker means warmer
* thicknessmm — Entire series: thicker means warmer
* darksum — Entire series: thicker means warmer
Thus:
* xraydenseave — Pre-1720, Mann disagrees with Tiljander. Post-1720, disagree
* lightsum — Pre-1720, Mann disagrees with Tiljander. Post-1720, disagree
* thicknessmm — Pre-1720, neither agree nor disagree. Post-1720, disagree
* darksum — Pre-1720, Mann agrees with Tiljander. Post-1720, disagree
I’ll point out that Mann08 uses lightsum, thicknessmm, and darksum as if they are three independent data series. They are not, because darksum is simply thicknessmm minus lightsum. (The use of natural-log transforms of these series unfortunately obscured this for some time.)
Finally, I will caution that Tiljander03’s interpretations of XRD, lightsum, and darksum are plausible, but they are not necessarily correct. My own view is that these series aren’t suited for use as temperature proxies, as discussed here. Search for “Regarding another question” and note that the Little Ice Age is clearly visible in the profile of Chironomid fossils from Lake Hamptrask. No clear-cut changes in any of the Tiljander data series from nearby Lake Korttajarvi are evident.
Thanks for an interesting analysis, AMac, that points out some of the problems that exist not just with the Tiljander proxies but with many other proxies.
The problem with the Mann method is that he seems to just wander around looking at proxies and picking ones that fit his theories. In truth, it’s hard to find anything that’s a good proxy for temperature. I mean, consider the difficulty that humans had in coming up with a proxy to measure temperature before finally settling on the expansion of mercury with temperature. And that’s before we get to questions of confounding variables.
Your contribution, as always, much appreciated.
w.
AMac, thanks for the cite, I’d forgotten about the whole episode at Collide-A-Scape where Gavin Schmidt came in all full of bravura and disappeared without comment midstream when you asked him the tough questions …
And I loved Mosh’s comment there, viz:
Yep. Sure enough. The team seems to feel that if they admitted one mistake the rot would set in … while never seeming to realize that the unwillingness to admit mistakes IS the rot …
w.
Mikael Pihlström says:
June 2, 2011 at 5:22 am
Mikael, as with the endangered species question, again you are being deceived by what the scientists say, as opposed to what they show.
But what they show in Figs S4A & B is very, very different. There’s a good discussion of the issues with Salzer here. Read it beginning to end, and then come back and tell us exactly where it is wrong, quoting what you think is objectionable or incorrect and then telling us exactly why it is incorrect. (Or, you could just quietly leave without either reading it or commenting on it. However, I must warn you that people will judge you on your actions.)
Back to Salzer, their upper figure (S4A) shows the raw tree ring widths for stripbark (solid lines) and regular (dotted lines) bristlecones, while the lower figure shows the results after standardization. They claim that the problem with the modern data is due to improper standardization (despite the fact that the original authors used the industry-accepted techniques).
But if you look at the data, they’re just blowing smoke. The difference between the two datasets, whole- and strip-bark, exists whether they are “standardized” or not. All the standardization does is shift the disagreement from early to late.
So while their statement is true on its face, that “when their raw ring widths are plotted in the same manner as our Fig. 3, there is little difference between their strip-bark and whole-bark groups in the modern period”, it is also very deceptive because when there is no difference in the modern period there is then a huge difference in the earlier period.
Mikael, I understand both your frustration and your desire to set things straight. But you have to get about 723 times more doubtful and about 635 times less trusting of climate science papers. The authors, as in this case, often have a huge axe to grind—to take just one example, Hughes is one of the co-authors of the Hockeystick paper. Do you really think that he will present an unbiased case? Because I can assure you that he won’t. Your job is not to read their claims and go “Yep, uh-huh, that sounds right”.
Your job is to go through line by line, ignore their claims and their interpretations, look at their actual results, and then judge for yourself whether their claims and interpretations of the actual results are correct.
And if you are not competent to do that … then why are you bothering us by simply parroting their claims without (apparently) the slightest attempt to see if they are worth more than a bucket of spit? It has been demonstrated over and over that there are many mainstream AGW scientists including some of the biggest names who are willing to lie, cheat, and steal to convince people that they are right.
And you simply believe them? At one time, that could have been reasonable ascribed to ignorance of their habits and their motives.
But to still blindly believe them in the year 2011, to swallow their claims without the simplest attempt to check their validity?
That’s serious selective blindness, Mikael, and it doesn’t redound to your credit.
Two problems there. The “new tree ring sets” get mixed with the old standard bogus hockeystick sets, so they can still get hockeysticks.
More to the point, the bristlecones are not “generally disqualified because the sceptics say so”. They are disqualified because, as the NAS and a number of other researchers in the field have repeatedly pointed out, they a) don’t agree with all the rest of the proxies, and b) have failed replication.
The reason for this is obvious to some of us. When part of a tree’s bark is gone, all of the growth occurs under the bark that remains, and inevitably the tree rings there will be wider than they were when the tree had its whole bark … duh, it’s not rocket science.
But then we’re not rocketing around trying to cooper up the holes in a failed theory. Mikael, you are putting your trust in people who will very happily deceive you, and by all appearances they have succeeded. Truly, you need to become as skeptical of your side of the debate as you are of the other side, because those “friends” on whose word you are depending are looking out for their own necks and not for the truth.
w.
“So overall I don’t think cluster analysis would be much help there. All you would end up saying is “well, the tides in the Solomons are most like the tides in X”, but that doesn’t help much.”
You think too much, for one thing, ha ha. Perhaps your method is not indeed the best display of what I noticed in individual tide gauges, but what I saw your method’s strength as was that it exposed how the majority of underlying data failed to show a hockey stick, so my suspicion is that the vast majority of tide gauges would not scatter all over the place into little islands of local effect, but in fact form a mega-cluster that lacked much trend change at all, thus exposing the potential fact that only a few do show much recent trend change. Of course I would want to simply ignore records that did not carry back a full century or so, long enough to contain within each of them the true historical trend prior to the modern one. I’m onto something here (after six hours of tide gauge browsing), and am fishing for the best expression of it that is also rigorous and immune to observer bias.